The selection of ground motion models, and the representation of their epistemic uncertainty in the form of a logic tree, is one of the fundamental components of probabilistic seismic hazard and risk analysis. A new ground motion model (GMM) logic tree has been developed for the 2020 European seismic hazard model, which develops upon recently compiled ground motion data sets in Europe. In contrast to previous European seismic hazard models, the new ground model logic tree is built around the scaled backbone concept. Epistemic uncertainties are represented as calibrations to a reference model and aim to characterise the potential distributions of median ground motions resulting from variability in source scaling and attenuation. These scaled backbone logic trees are developed and presented for shallow crustal seismic sources in Europe. Using the new European strong motion flatfile, and capitalising on recent perspectives in ground motion modelling in the scientific literature, a general and transferable procedure is presented for the construction of a backbone model and the regionalisation of epistemic uncertainty. This innovative approach forms a general framework for revising and updating the GMM logic tree at national and European scale as new strong motion data emerge in the future.

中文翻译：

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针对欧洲浅层地震的区域适应性“比例骨干”地震动逻辑树：在2020年欧洲地震灾害模型中的应用

地震动模型的选择以及以逻辑树的形式表示它们的认识不确定性，是概率地震危险性和风险分析的基本组成部分之一。为2020年欧洲地震灾害模型开发了新的地面运动模型（GMM）逻辑树，该逻辑树是基于最近在欧洲编辑的地面运动数据集而开发的。与以前的欧洲地震灾害模型相比，新的地面模型逻辑树围绕缩放的主干概念构建。认知不确定性表示为对参考模型的校准，旨在表征源尺度和衰减的变化所导致的地中运动的潜在分布。这些缩放的主干逻辑树是针对欧洲浅层地壳地震源开发和提供的。使用新的欧洲强运动平面文件，并利用科学文献中地震动建模的最新观点，为骨架模型的构建和认知不确定性的区域化提供了一种通用且可转移的程序。随着未来出现新的强劲运动数据，这种创新方法形成了在国家和欧洲范围内修订和更新GMM逻辑树的通用框架。